LET-381/FoxF and UNC-30/Pitx2 control the development of C. elegans mesodermal glia that regulate motor behavior.

Posted by dbos Rockefeller

Kavli Affiliate: Shai Shaham | Authors: Nikolaos Stefanakis, Jessica Jiang, Yupu Liang and Shai Shaham | Summary: While most CNS glia arise from neuroectodermal progenitors, some, like microglia, are mesodermally derived. To understand mesodermal glia development and function, we investigated C. elegans GLR glia, which ensheath the brain neuropil and separate it from the circulatory-system […]


Continue.. LET-381/FoxF and UNC-30/Pitx2 control the development of C. elegans mesodermal glia that regulate motor behavior.

Honey varietals differentially impact Bifidobacterium animalis ssp lactis survivability in yogurt through simulated in vitro digestion

Posted by dbos Hopkins

Kavli Affiliate: Michael Miller | Authors: David A. Alvarado, Luis Alberto Ibarra-Sanchez, Annemarie R. Mysonhimer, Tauseef A Khan, Rong Cao, Michael J. Miller and Hannah Holscher | Summary: Background Bifidobacterium animalis ssp. lactis DN-173 010/CNCM I-2494 (B. animalis) is a probiotic strain commonly added to yogurt. Yogurt and honey are a popular culinary pairing. Honey […]


Continue.. Honey varietals differentially impact Bifidobacterium animalis ssp lactis survivability in yogurt through simulated in vitro digestion

Context-invariant socioemotional encoding by prefrontal ensembles

Posted by dbos UCSF

Kavli Affiliate: Vikaas Sohal | Authors: Nicholas A Frost, Kevin C Donohue and Vikaas Sohal | Summary: The prefrontal cortex plays a key role in social interactions, anxiety-related avoidance, and flexible context- dependent behaviors, raising the question: how do prefrontal neurons represent socioemotional information across different environments? Are contextual and socioemotional representations segregated or intermixed, […]


Continue.. Context-invariant socioemotional encoding by prefrontal ensembles

SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

Posted by dbos Tokyo

Kavli Affiliate: David Spergel | First 5 Authors: Pablo Lemos, Liam Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg | Summary: We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_ell$, with analytic models based […]


Continue.. SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multi-dimensional supernova simulations

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

Posted by dbos Tokyo

Kavli Affiliate: Shunsaku Horiuchi | First 5 Authors: Nick Ekanger, Shunsaku Horiuchi, Hiroki Nagakura, Samantha Reitz, | Summary: The sensitivity of current and future neutrino detectors like Super-Kamiokande (SK), JUNO, Hyper-Kamiokande (HK), and DUNE is expected to allow for the detection of the diffuse supernova neutrino background (DSNB). However, the DSNB model ingredients like the […]


Continue.. Diffuse supernova neutrino background with up-to-date star formation rate measurements and long-term multidimensional supernova simulations

${rm S{scriptsize IM}BIG}$: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering

Posted by dbos Tokyo

Kavli Affiliate: David Spergel | First 5 Authors: ChangHoon Hahn, Pablo Lemos, Liam Parker, Bruno Régaldo-Saint Blancard, Michael Eickenberg | Summary: The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy […]


Continue.. ${rm S{scriptsize IM}BIG}$: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez | Summary: It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing […]


Continue.. Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez | Summary: It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing […]


Continue.. Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects